Cognitive Modeling of Web-Navigation and Information Search
Investigating the influence of cognitive factors affecting web-navigation/information search and modeling them.
CoLiDeS+ Processing Model
Schematic diagram of steps involved in CoLiDeS+: Shaded circles indicate the locations where individual differences are involved (1: Age, 2: Domain Knowledge, 3: Spatial Ability and 4: Need for Cognition).
Why this research mattered
Information search and web-navigation involve several cognitive processes such as memory, attention, problem solving, comprehension and decision making. These cognitive processes are known to be affected by one or more cognitive factors such as aging, domain knowledge and presence of graphical information on the pages. Understanding how the process of information search and navigation works and how it is influenced by one or more of the factors enables development of automated support tools that enhance performance.
"How to cognitively model the individual factors that influence web-navigation and information search?"
This research program investigated the cognitive processes underlying user navigation on websites and information search using search engines. This research developed and validated computational cognitive models to predict user clicks on websites, search query reformulations and clicks on search engine results.
Experiments, A/B Tests
Experiments investigating the influence of individual factors like age, domain knowledge and presence of graphical information on websites
Cognitive Modeling
Enhancing cognitive models with learnings from experiments to incorporate individual differences of age, domain knowledge and graphical information
Simulations
Run simulations of the enhanced models and compare with actual behavior
Build Support Tools
Build a predictive support tool using the enhanced computational cognitive models and evaluate their efficacy.
Research Program
Connected studies conducted progressively answered different aspects of the central research question.
CoLiDeS + Pic Model
"How does graphical information on websites influence navigation behavior, and how to model it?"
Enhanced cognitive model of web-navigation that incorporates semantic information from pictures and a support tool for web-navigation based on the enhanced model
Modeling individual differences (age, domain knowledge) in information search
"How do age and domain knowledge influence information search behavior and how to model them?"
Enhanced cognitive model of information search that incorporates age and domain knowledge differences and a support tool for information search based on the enhanced model
Role of Domain Knowledge in Cognitive Modeling of Information Search
Background
Cognitive models of information search (back then) did not incorporate individual differences in information search behaviour caused by differences in domain knowledge. This research filled that gap by first experimentally establishing that domain knowledge differences cause differences in information search behavior, enhanced the cognitive model to incorporate domain knowledge affects, ran simulations with the enhanced model and compared the simulations with actual user behavior.
Research Questions
- How to incorporate differences in domain knowledge levels of users into a computational cognitive model that predicts information search behavior?
- Would a model that takes differences in domain knowledge into account, predict user clicks on search engine result pages better than a model that does not?
Research Approach
Key Findings
Interaction of semantic space x domain knowledge of actual users
The efficacy of the modeling (in terms of the number of matches between model predictions and actual user clicks) was higher with the expert semantic space compared to the non-expert semantic space while for low domain knowledge participants it was the other way around
Interaction effect is lost if two different semantic spaces were not used
A plausible explanation for the interaction effect is that the expert and the non-expert semantic spaces give appropriate similarity values as assessed by users with high (more precise) and low (less precise) domain knowledge respectively
What We Learned
Learnings from this program
Effect of graphics/pictures
The accuracy of user navigation behavior is better when the semantic information from graphics/pictures on a web-page is highly relevant to the content of the page.
Effect of age
Older adults generate less search queries, use less keywords per query, reformulate less, spend longer time evaluating the search results, spend more time evaluating the websites opened and switch less often between search results and websites.
Effect of domain knowledge
Users with higher domain knowledge have more appropriate mental representations characterized by more relevant concepts, higher activation values, stronger connections between concepts. Users with higher domain knowledge therefore can comprehend the search results and content of websites better.
Enhanced cognitive models
Models that incorporate individual differences in search and navigation behavior due to differences in cognitive factors such as age and domain knowledge predict actual behavior with greater accuracy.
Research Artifacts
Empirical assets and frameworks generated to guide future enterprise-wide design and engineering direction.
Cognitive models
CoLiDeS+Pic computational simulations mapping visual-semantic parsing. CoLiDeS+ - with variations that mimic individual differences in age and domain knowledge
LSA semantic spaces
Two semantic spaces with high and low health related information
Experimental results
Results of several A/B Tests investigating the influence of pictures, age and domain knowledge on web-navigation and information search
Support tools
Support tools based on the enhanced cognitive models
Program Portfolio
A portfolio of experiments, simulations and support tools exploring cognitive web-navigation and information search.